Optimizing Eco-Efficiency Across the Procurement Portfolio

Article pubs.acs.org/est

Optimizing Eco-Efficiency Across the Procurement Portfolio Rylie E. O. Pelton,† Mo Li,† Timothy M. Smith,*,† and Thomas P. Lyon‡ †

NorthStar Initiative for Sustainable Enterprise, Institute on the Environment, University of Minnesota, 325 Learning and Environmental Sciences, 1954 Buford Ave, Saint Paul, Minnesota 55108, United States ‡ Erb Institute for Global Enterprise, University of Michigan, 701 Tappan Street, Ann Arbor, Michigan 48109, United States S Supporting Information *

ABSTRACT: Manufacturing organizations’ environmental impacts are often attributable to processes in the firm’s upstream supply chain. Environmentally preferable procurement (EPP) and the establishment of environmental purchasing criteria can potentially reduce these indirect impacts. Life-cycle assessment (LCA) can help identify the purchasing criteria that are most effective in reducing environmental impacts. However, the high costs of LCA and the problems associated with the comparability of results have limited efforts to integrate procurement performance with quantitative organizational environmental performance targets. Moreover, environmental purchasing criteria, when implemented, are often established on a product-by-product basis without consideration of other products in the procurement portfolio. We develop an approach that utilizes streamlined LCA methods, together with linear programming, to determine optimal portfolios of product impact-reduction opportunities under budget constraints. The approach is illustrated through a simulated breakfast cereal manufacturing firm procuring grain, containerboard boxes, plastic packaging, electricity, and industrial cleaning solutions. Results suggest that extending EPP decisions and resources to the portfolio level, recently made feasible through the methods illustrated herein, can provide substantially greater CO2e and water-depletion reductions per dollar spend than a product-by-product approach, creating opportunities for procurement organizations to participate in firm-wide environmental impact reduction targets.

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INTRODUCTION Motivated largely by cost minimization and access to new markets,1 organizations increasingly assemble complex and fluid-supply networks, connecting global market, logistics, and financing systems to local raw materials, labor, and distribution resources.2−4 As a result, supply-chain management has become increasingly important to the success and long-term viability of global firms.5,6 Recent advances in global supply-chain management offer rapid response systems for supply-chain managers to quickly reconfigure supply and production networks to meet changing consumer demands, commodity prices, and currency fluctuations.7,8 However, as firms have sought competitive advantage through these strategies, they have also found significant risk and complexity associated with reputational and operational performance in the supply-chain function.9−12 In response, many firms are turning to sustainable-supplychain management (SSCM) and environmentally preferred procurement (EPP) in an attempt to reduce these risks, recognizing the need to influence operations that fall outside of their direct control. Highly publicized efforts from across the value chain, from retail to raw-material production, exemplify this trend: Walmart’s Sustainability Scorecard, Tesco’s sustainable-supply-chain Knowledge Hub, the Sustainable Apparel Coalition, the Electronic Product Environmental Assessment Tool, the Green Suppliers Network, and the Forest Stewardship Council, to name only a few.13−21 Although sustainable© XXXX American Chemical Society

supply-chain integration can help align values and norms of suppliers with the strategic goals of downstream firms,22,23 implementing and assessing environmental procurement criteria is not straightforward.24−28 Two primary gaps persist between intention and the implementation of high-performing sustainable supply chains: (1) the relatively high transaction costs associated with identifying and procuring greener products; and (2) a lack of comparative information available to guide decision-makers confidently toward more cost-effective environmental benefits.29−31 Increased pressures on supply chain managers to incorporate sustainability metrics into operational decisionmaking have created an increased demand for environmental and social information about suppliers’ goods and services,32 resulting in a growing number of standards and certifications that designate “environmentally preferable” purchasing options. These tools are an accessible and simple way for purchasers to “buy green,” but the proliferation of eco-labels and other sustainability messaging has also caused concerns over the accuracy of claims and has led to worries about a backlash over greenwashing and buyer confusion.33 Received: December 28, 2015 Revised: May 9, 2016 Accepted: May 10, 2016

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DOI: 10.1021/acs.est.5b06289 Environ. Sci. Technol. XXXX, XXX, XXX−XXX

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Environmental Science & Technology

environmental benefits under specified budget constraints. This approach, termed hotspot scenario analysis−procurementportfolio optimization (HSA−PPO), significantly contributes to the EPP and sustainable supply chain literatures by demonstrating approaches that facilitate EPP both within product categories and across the procurement portfolio, thereby providing methodological advances to previously intractable knowledge gaps. Although using a systems (portfolio) approach is relatively new to EPP, its utility has been demonstrated and advocated for in several other areas. For example, several authors demonstrate the benefits of a portfolio approach in manufacturing, where all possible production pathways are considered in the design of optimal co-product portfolios.50−53 Other authors advocate for using a portfolio approach in LCA instead of traditional single-product approaches, particularly as it relates to the potential to capture the temporal distribution of impacts.54,55 Organizational LCA (O-LCA), which is an evaluation of the environmental performance of an organization, is another manifestation of a portfolio approach, requiring organizations to consider their entire portfolio of suppliers and distributors across all operating units.56 This study contributes to the literature on portfolios by assessing the relative environmental performance of a portfolio approach compared to a product-by-product approach in the implementation of EPP. In doing so, we highlight the potential for increased coordination of sustainability strategies across procurement and sourcing functions to most effectively and efficiently reach organizational sustainability objectives.29 We begin by describing the application of the HSA approach to a simulated procurement portfolio for a breakfast cereal (BFC) manufacturing firm, which procures eight product categories: electricity, wheat grain, corn grain, plastic bags and paperboard boxes for primary packaging, plastic films and corrugated board boxes for secondary packaging, and cleaning compounds. We then develop a linear programming model for the application of the procurement-portfolio optimization (PPO) approach to explore combinations of product environmental attributes across the portfolio that maximize environmental performance under departmental and organizational budget constraints. Finally, we present the results of the HSA− PPO method and explore sensitivities of the approach to uncertainties across product price assumptions, HSA assumptions, and changes in procurement budget.

A number of efforts to create more standardized frameworks for green-product claims have emerged in recent years, ranging from the European Union’s Integrated Product Policy process34 to ISO standards for the creation of LCA-based productcategory rules (PCRs). However, assessing sustainability performance remains a difficult and costly task. Within the U.S. context, the U.S. EPA established a multistakeholder effort in 2015 to pilot and offer recommendations to develop transparent, fair, and consistent approaches to selecting environmental performance standards and eco-labels to support federal sustainable acquisition mandates.35 This endeavor, as with many other initiatives across industry groups and retailers, approaches product environmental performance on a product category by product category basis (e.g., paints, flooring, furniture, etc.). Although necessary from the perspective that the efficacy of environmental improvement strategies vary across product systems, corporate and institutional procurement organizations often purchase thousands of products across hundreds of product categories. Identifying the product inputs on which to focus resources and determining purchasing strategies targeting improved eco-efficiencies remains a daunting proposition for sourcing managers.7 Environmental assessment competencies have been slow to infiltrate strategic sourcing and procurement organizations, in large part due to the cost-minimizing cultures of these functions and the high transaction costs associated with searching and screening the “credence” qualities associated with environmental performance.36−40 In a growing number of organizations, environmentally extended input−output models (EEIO) have been deployed to help prioritize product categories for implementing environmental procurement criteria based on the relative environmental impacts associated with purchasing spending within each product industry.41,42 This approach also helps elucidate influential inputs and the life-cycle stages that most affect environmental performance of procured product categories. Huang et al. (2009) suggest that environmental performance improvements affecting these highimpact stages be considered more closely for their potential to provide the greatest overall impact reduction.41 However, issues remain in determining which product environmental claims or attributes are most effective at reducing environmental impacts without conducting costly life-cycle assessments and waiting sometimes years for results.43−45 Even when organizations have chosen to invest in understanding the environmental performance of procured products, significant challenges remain with regard to the comparability of supplier-provided information. These challenges occur both within product categories, e.g., comparing paper packaging inputs across competing suppliers,46 and between product categories, e.g., comparing initiatives to reduce the environmental burdens of procured paper versus procured plastics or aluminum across the procurement function.47 This is especially true under the typically specialized organizational structures of the corporate procurement and sourcing function, where individual purchasing departments responsible for buying particular product categories function as independent, siloed groups constrained by departmental budget targets.29,48 In this paper, we build upon the streamlined LCA methodologies developed previously in Pelton and Smith (2014)49 by applying the hotspot scenario analysis (HSA) approach across multiple procured product categories of a simulated strategic sourcing organization and developing optimal procurement portfolio strategies that maximize

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MATERIALS AND METHODS Hotspot Scenario Analysis. The eight product categories are prioritized for EPP based on their environmental impacts relative to other procured products and stakeholder interests.57−60 The environmental impacts of the procurement portfolio were estimated through environmentally extended economic input−output (EEIO) models59 using the Bureau of Economic Analysis (BEA) “Use Tables” to determine the quantity of dollars spent on each input industry for $1 million of BFC manufacturing output, thus representing an average BFC manufacturing firm.61 Due to the time and cost to conduct a full LCA, hotspot analysis methods were used to identify the hotspot stages and inputs that drive each prioritized product’s total impacts. These hotspots serve as the focal areas for parametrized process LCA, allowing several alternative scenarios to be assessed, as suggested by Huang et al. (2009) and demonstrated in Pelton and Smith (2014).41,49 The hotspots for each prioritized product were identified using EEIO and extant LCA literature and were limited to cradle-toB


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Table 1. Purchasing (Product) Category Hotspots, Environmental Product Attributes, and Product Option Rules for Attribute Combination

a

Nonexclusive attributes can be combined with other nonexclusive attributes and mutually exclusive attributes; however, attributes listed as mutually exclusive cannot be combined with other attributes listed as mutually exclusive. All attributes can be combined across hotspot stages within a product category. A product option can either be composed of a single attribute or a combination of attributes. Note that energy-efficiency attributes for electricity used in BFC manufacturing are not included in the set of available options as efficiency improvements cannot be influenced by procurement decisions but rather decisions made in the manufacturing function; therefore, only wind electricity is included as procurement is able to influence the type of electricity purchased.

corrugated board, have impacts that are driven by the pulp and paper-milling and box-manufacturing operations, as well as wood harvesting due to different forestry management practices that affect net carbon sequestration.59,65,66 Plastic packaging impacts are driven by resin manufacturing and product manufacturing, such as film or bag manufacturing, which thermally transforms plastic resins into final consumer products.59,67 Lastly, hotspots for cleaning compounds include the impacts from the formulation of input ingredients as well as packaging.59,68,69 See the Supporting Information for additional details. Each identified hotspot stage serves as the system boundary for a parametrized process-based analysis, which was conducted in the thinkstep GaBi 6.0 LCA software.70 Several sources were used to determine the quantities and types of material and

gate impacts (i.e., extraction of resources to the manufacture of final consumer products) to best represent the impacts that can be influenced by the procurement function. Hotspots were selected for further analysis if they contributed greater than 10% of the total cradle-to-gate impacts for a given impact category. This threshold was chosen to limit the number of sectors evaluated and to capture a significant enough portion of impact to make sustainability efforts worthwhile. The current study assesses impacts on global-warming potential (GWP) and water-depletion, primary areas for which organizations have set quantitative sustainability targets.62 Impacts from electricity are driven by the mix of fuels used.59,64 For grain, the farming operation is the hotspot for environmental impacts, particularly from nitrogen fertilizer inputs, on-farm fuel use, and irrigation water.58,59,63 Containerboard boxes, such as paperboard and C


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attributes, almost 600 combinations (i.e., product options) within and across hotspots were included in the optimization analysis (see the Supporting Information for a description of the attributes). Procurement Portfolio Optimization. Optimizing the EPP process requires information on both comparative environmental impacts and the cost to procure environmental product options. For each product category, the average baseline prices per unit (i.e., $/bushel, $/kWh, $/kg, and $/gal) of conventional products purchased were determined through a variety of literature and market sources.74−79 These sources were also used to determine whether each product environmental attribute yields a price premium or discount.74−80 In each product category, wholesale prices were used to reflect the typically lower prices obtained by industrial and commercial purchasers. Some attribute prices, such as those associated with wind electricity, electric efficiency, and thermal efficiency, were used for multiple product categories. For attributes that result in cost savings through the reduction of inputs, such as energy efficiency, it is assumed that the cost savings is shared equally between the input producer and the consumer, i.e., the BFC manufacturer, because a competitive advantage may be gained for the producer by lowering prices. The total price of each product option is determined through the sum of the relevant attribute-price premiums and discounts; adding one and multiplying these factors by the baseline prices determines the dollars per unit for each environmental product option (see Table S6). To optimally allocate procurement budget across product options and across the procurement portfolio, the total cradleto-gate impacts of the analyzed products must be known. To estimate such impacts without conducting costly full LCAs, we first determine the cumulative hotspot impact per dollar spent (HC) for each product category (C) by dividing the cumulative hotspot impacts per unit (hC) developed from process LCA models by baseline product unit prices (zC) (eq 1).

energy inputs required for each product hotspot stage (see the Supporting Information for details). The upstream life-cycle inventories of each identified material and energy input were provided by commercial databases such as ecoinvent,64 PE International,70 and USLCI;71 although using data from a single database is preferable to ensure comparability in product input system boundaries, a combination of the databases was used due to limitations in data availability. TRACI 2.1 and ReCiPE 1.08 methods were used to characterize GWP impacts and water depletion, respectively.72,73 For each hotspot, the conventional product impacts are modeled to represent U.S. averages, which serve as the baseline of comparison for products claiming environmental preferability. For each prioritized product, a variety of product environmental attributes that specifically relate to the product hotspot stages and inputs were identified through the examination of market claims, eco-labels, and literature (Table 1). These attributes either represent a reduction or increase in certain types of inputs or substitutions of processes and inputs with alternative processes and inputs. In each case, the goal is to illustrate the greatest potential magnitude of impact reductions feasible for organizations to achieve through strategic sustainability investments. For each attribute, the percent changes in environmental impacts relative to the baseline impacts are determined. These percent reductions or increments in impact are multiplied by the estimated percentage that each hotspot stage contributes to the total impacts of each purchasing category, as determined through a combination of EEIO and literature review. Because the EEIO hotspot percentage estimates are representative of broad industry impacts, these percentage values are averaged with estimates obtained from the literature because processbased LCA is often at the more-specific product-category level.49 This results in an approximation of the potential for an attribute to reduce the total cradle-to-gate impacts of the prioritized product categories (see Table S6). In each hotspot stage, some attributes can be combined, while others are mutually exclusive. For example, the percent change in impacts as a result of organic farming methods cannot be combined with the percent change in impacts from precision farming methods because different inputs and quantities of inputs are used in the two farming systems. A product option can either represent a single attribute or a combination of attributes (Table 1). The number of mutually exclusive attributes can be minimized, resulting in a greater number of possible product options, if the combination of attributes is considered directly in the process-based LCA models, thereby accounting for the nonlinearity of environmental impacts. Due to time constraints, however, the current study allows mutually exclusive attributes to dictate possible attribute combinations. Attributes can also be combined across stages, as they are implemented in completely different processing stages; thus, issues of exclusivity do not apply for the combination of attributes across hotspot stages. For example, attributes from the wood-harvesting stage, which describe the intensity of the growing and harvest operation and are mutually exclusive, can be combined with attributes from the paper mills and box-manufacturing stages. The sum across all attribute percent reductions or increments, after multiplying by the percent contribution of each respective hotspot, represents the total effect of each product option on the total cradle-to-gate impact of each purchasing category. Even allowing for mutually exclusive product environmental

hC = HC zC

(1) C

The cumulative hotspot impact per dollar (H ) can then be divided by its cumulative hotspot percent contribution to total cradle-to-gate impacts (pC), which results in an estimate of the total cradle-to-gate impacts per dollar spent (IC) on each product category (eq 2): HC = IC pC

(2)

This value can then be multiplied by the total spend on each purchasing category (SC) to determine the total cradle-to-gate impacts (TC) associated with organizational procurement for the selected portfolio of products (eq 3). For the current study, the dollars spent on each product category, SC, are estimated by the relative product output within each industry using BEA economic input−output item tables;60 this step would be unnecessary if actual information on procurement spend were available. I C × SC = T C

(3)

Because trade-offs often exist between environmental impact categories, making decisions difficult, an environmental performance index (EPI) was created using normalized values of GWP and water depletion weighted to reflect their relative D


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Figure 1. Results of hotspot scenario analysis: a comparison of product options across environmental impacts and cost. Product options spread along the dimensions of costs and environmental impacts (GWP, water depletion, and environmental performance index) relative to each product category’s baseline costs and environmental impacts. Bubble size of each product category labels indicate the relative amount of dollars spent on each purchasing category, which plays a significant role in the final capital resource allocation to product options resulting from the optimization analysis, as it dictates the budget available for EPP across each purchasing category. Note that the total spend per purchasing category does not sum to 100% as these eight product categories represent a prioritized subset of the total procurement product budget. Although product options are based on individual attributes that are believed to be currently available on the market, some combinations of attributes may not yet be assembled on the market but instead may represent future product options that could be brought about through leveraging the role procurement and sourcing managers have with suppliers to impact the options available in the marketplace.

programming (LP) method and was constructed in the R Project software using the lpSolveAPI package.84 The model operated under the assumption that the total quantity purchased in each product category must stay consistent with the quantities purchased preoptimization because the procurement function must ensure sufficient amount of product inputs into the BFC manufacturing process to maintain a consistent output. To demonstrate the potential benefits of coordinating EPP across the procurement portfolio through a strategic management process, we first ran the optimization model under the assumption that product category purchases are made by individual departmental silos and then run assuming procurement is coordinated across the organization’s product category portfolio through strategic management and planning. In the case of purchasing silos, each purchasing department, C, has a set of different product options available in the market, i = 1,...,MC, chooses a quantity of each product, nCi , to minimize the environmental impacts (GWP, water depletion, or EPI) for the

importance to management, as determined by internal or external stakeholder preferences or government or scientific recommendations. The normalization references represent the U.S. total quantity of GHGs emitted and total water depleted in a year, 7.771 billion tons of CO2e81 and approximately 3.82e10 kGal per year,82 respectively. Each normalized GWP and water depletion value is then multiplied by its respective weighting factors to create an EPI. The weighting factors used in the current study were developed for the purpose of environmentally preferable purchasing in the U.S.83 and were determined through stakeholder (including producers, users, and LCA experts) preferences, which were systematically prioritized via the analytic hierarchy process (AHP) and resulted in the recommended weights for GWP (CO2e) as 29% and 8% for water depletion. Note that the weights do not sum to 100% because other impact categories prioritized in the AHP were not included in the current study but could be included in the future. The final step in the HSA−PPO method is the construction of the optimization model. The model is based on the linear E


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Figure 2. Results of procurement optimization: comparative reductions in environmental impacts and spending for silo- and portfolio-procurement approaches. A comparison of the GWP, water-depletion, and Environmental Performance Index impact reductions and increments (relative to baseline) for each product category under the silo- and portfolio-procurement approaches, where the objective is to minimize environmental impacts subject to particular budgetary constraints. Total procurement spending and environmental impacts across the eight purchasing departments are indicated to the right of the red dotted line. Intraorganizational cap and trade activities are well-illustrated in the electricity-, corn-grain-, and paperboard-purchasing departments by comparing spending and environmental reductions achievable through the portfolio approach to the silo approach. Because the budget constraints in the silo approach prevent some categories from purchasing more expensive product options to achieve reductions, the marginal contribution to the objective (shadow price) is higher than the silos that are able to access reduction opportunities within the budget (see Table S9). i=1

department while staying within the departmental budget and meeting the departmental output requirements NC (eq 4):

minC {∑ ∑ EICi × niC} subject to:

{{niC}iM= 1 }C

C i=1

i=1

minC{∑

{niC}iM= 1 M C i=1 PiC C M

∑

EICi

×

niC}

∑∑

subject to:

C

MC

MC

i=1

PiC

×

niC

O

≤B ,

∑ niC = N C MC

(5)

i=1

× niC ≤ BC ,

∑ niC = N C MC

In this study, the total baseline procurement financial expenditures across all prioritized product categories for the BFC manufacturing firm is $128,258, calculated based on the relative spend on product inputs for $1 million of BFC output.61 The output from the optimization model results in the optimal quantity of each product option (nCi *) that procurement resources should be allocated toward, given the model parameters. After the total spending and impacts across all purchasing categories are aggregated, both the silo and portfolio approaches are compared to the baseline performance, where only conventional products are purchased, to illustrate the comparative ability of the portfolio versus silo approaches to reduce the total quantity of the organization’s impacts and the resulting effects on the total financial expenditures of the organization. See the Supporting Information for a list of the methodological steps, example calculations, and parameters.

(4)

where EICi is the environmental impact per unit of product option i, PCi is the unit price of product i, and BC is the departmental silo’s procurement budget for a purchasing category. For the coordinated portfolio approach, the eight departments are managed across product categories to meet the organization’s overall performance targets. Each purchasing department, C, chooses a quantity of each product, nCi , from the same set of available product options, i = 1,...,MC to minimize the environmental impacts for the organization while staying within the total organizational procurement budget, Bo, across the portfolio of prioritized products (eq 5) and meeting output requirements NC for each department: F


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RESULTS The parametrized LCA results suggest that some product attributes reduce impacts and some increase impacts relative to conventional baseline product impacts, which in some cases vary between the GWP and water-depletion impact categories. For example, for the cleaning-compound category, GS37 products (those that meet Green Seal Standard formulations for industrial and institutional cleaners) were found to increase the GWP impact but reduce the water-depletion impact relative to conventional cleaning compounds over the cradle-to-gate life cycle due to the particular ingredients involved in its formulation, thereby representing trade-offs in the environmental preference of such products. It is important to note that trade-offs may exist in other impact categories, such as human and ecotoxicity impacts, acidification, eutrophication and so forth, but they can be considered while making procurement decisions using an EPI based on the relative importance to manage each impact category. Results also show significant variability between attributes and attribute combinations in the magnitude of possible reductions or increments of impact (Table S2). It is important to mention that this study does not consider co-product displacement credits in the assessment of product options. Such credits may be received, for example, for the displacement of nitrogen fertilizers in organic farming systems or for the displacement of conventional electricity mixes in semi self-sufficient mills using pulp fiber. Therefore, if these co-products had been considered in the current study, the environmental profile of some product options may be lower than currently indicated, such as for grain organic attributes and containerboard recycled-content attributes (see the Supporting Information). For each product option, trade-offs between environmental impacts and costs must be considered, as some products may be environmentally preferable but cost significantly more than conventional or alternative product options and vice versa. Figure 1 displays the range of product options across purchasing categories along the dimensions of costs and environmental impacts, which are normalized against baseline costs and impacts. The figure clearly shows that several products result in win−win situations, meaning that both environmental impacts and costs can be reduced (the third quadrants), and several other products result in lose−lose situations, in which they both increase impacts and costs (the first quadrants). The second and fourth quadrants reveal tradeoffs between impacts and costs. Why certain product options result in higher or lower impacts is a result of the associated changes made in baseline inventory input quantities and types of inputs used (see the Supporting Information for details). The optimization model uses the product options indicated in Figure 1 as inputs and provides results suggesting that both silo and portfolio procurement approaches select products somewhat differently from the baseline case (Table S3). The potential purchasing strategies lead to significant reductions in total GWP, water depletion, and EPI for both the silo and portfolio approaches compared to the baseline performance. Figure 2 shows the detailed breakdown of total spending per category and total organizational spending for the portfolioand silo-procurement approaches and the corresponding quantities of reductions and increments for GWP, waterdepletion, and EPI impacts as compared to the baseline. The figure reveals that the silo approach can help cut the company’s financial budget by 0.25% to 2.54% and reduce 24% to 28% of

environmental impacts, depending on the impact category being minimized. The portfolio approach increases the range of impact reductions to between 37% and 38% by using the dollars saved in some product categories to gain additional environmental improvements in other categories while staying within the total organizational budget. This intraorganizational “cap and trade” process is clearly evident in the electricity and corn-grain purchasing categories in Figure 2. Under the silo approach, no changes are made to purchasing relative to the baseline in these product categories due to the inability to access higher cost environmental product options under the silo budget constraints, but the portfolio approach reallocates spending from other purchasing departments to these departments to achieve 10%, 13%, and 13% greater aggregate reduction relative to baseline in GWP, water depletion, and EPI, respectively. See Table S3 for the optimal resource allocation selected for each product category. The portfolio approach spends the entire budget allocated to EPP, while the silo approach fails to do so due to a skew in the product options available in particular silos. These results demonstrate, however, that the primary advantage of the portfolio approach is that it removes departmental budget constraints that may create barriers to efficient investments. Even low-cost opportunities may require substantial capital investments, which may be impossible to obtain within departmental silos due to budget constraints. Thus, the portfolio approach to EPP creates greater flexibility and therefore is more effective in reaching sustainability reductions (in this case, between 36% to 54% more effective). Although the resulting sustainability improvements are optimal under the current suite of product options, the optimization model could provide significantly different optimal solutions given a different or greater variety of product options with potentially different costs and environmental impacts, which may be an avenue for future research. Optimal solutions may also change given different budget scenarios; however, Figure S1 shows that strategically planning EPP budget allocations across purchasing departments is environmentally preferable among several budget scenarios. The figure further suggests that, by reallocating departmental budgets to reflect final spending allocations of the portfolio approach, significant managerial changes to the procurement function may be unnecessary because silo managers can achieve equal performance to the portfolio approach when higher-cost- and higherimpact-reduction product options are accessible under the optimal portfolio spend allocation. The concept of eco-efficiency is helpful in understanding the relative benefits of the portfolio-purchasing approach versus the typical silo-procurement approach. We compare the overall purchasing costs and environmental benefits for the two EPP approaches by using the metric of environmental costeffectiveness, which is defined as the total environmental impact per dollar spent on each product category.85 Using this metric, a lower eco-efficiency score for a given impact category is preferable to a higher score because it implies smaller overall environmental impact per dollar spent. Comparing the ecoefficiencies for each case to the baseline eco-efficiency (i.e., conventional product impacts and prices) gives the marginal change in total impacts per dollar when resources are allocated optimally in the silo and portfolio procurement approaches.85,86 For GWP, water depletion, and the index, the silo approach improves eco-efficiency by 27.5%, 23.2%, and 21.9%, respectively, whereas the portfolio approach improves ecoG


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assuming that there is some flexibility for product substitutions within organizational infrastructure. This is an interesting question for future research. Regarding uncertainty, much of the uncertainty around the comparability of process LCA models can be reduced using parametrization, which can help minimize the differences in assumptions and data sets across process LCA models. However, using the cumulative hotspot percent contribution to total impact as a way to estimate total product impacts can result in potentially significant uncertainty in the optimal allocation of resources among product options due to its effect not only on total impact characterization but also on the performance of product attribute options. A sensitivity analysis exploring this uncertainty, however, revealed that despite some changes in the optimal allocation of resources to different product options under differing hotspot percent assumptions, the portfolio approach to EPP always performs markedly better than the silo approach (Table S5). In fact, the silo approach can never outperform the portfolio approach because adding constraints to an optimization problem can never improve the objective. Furthermore, we recognize the influence that alternative spend distributions among product categories may have on the selected product options and the total minimized environmental impacts. In addition to the direct sensitivity assessment of alternative spend, budgetary shadow prices (i.e., the change in environmental impacts for each additional dollar spend in the budget, as determined by the optimal selected product options) and the budgetary range over which they remain valid can help characterize this uncertainty, as they indicate the stability of the selected optimal product options to changes in budgetary spend allocations (Table S9). We also provide shadow prices on product unit requirements, which indicate the incremental environmental-impact reductions of fewer units of product required, and the range of unit requirements over which the shadow prices are constant (Table S10). Comparing the portfolio to the silo approach, we find greater stability in product selection across possible budgets and unit requirements and continually lower shadow prices than in the silo approach, thus indicating the greater efficiency with which the portfolio approach takes advantage of reduction opportunities. Overall, the results across all analyses further substantiates existing literature supporting the use of portfolio-based analyses instead of single-product analyses for decision making and suggests that such a structure may be useful for procurement functions to transition toward for efficiently achieving environmental-performance targets. The results of this study show that the HSA−PPO method fills an important information gap by providing resource-limited organizations practical insight on the relative benefits of different product options across a portfolio of prioritized products. Importantly, the method helps reduce the two primary barriers to the implementation of EPP in practice, transaction costs, and comparability, thereby facilitating the participation of environmentally preferable purchasing in sustainable-supply-chain management and enabling organizations to more cost effectively and efficiently reach their sustainability performance objectives.

efficiency by 37.5%, 37%, and 36.7%, respectively, indicating the relative preferability of the portfolio approach for an EPP context. To test the sensitivity of the results to changes in the input assumptions, we ran the optimization for several alternative sets of parameters, including alternative attribute pricing, alternative product category spending, and alternative hotspot assumptions, which in turn changes total product category impact estimates and environmental product option performance estimates (see Tables S6 and S7). These alternative hotspot assumptions represent the minimum and maximum hotspot contributions to total impact found across all analyzed sources, which allows exploration of the effect of uncertainty in these estimates on the relative performance of the approaches. Not surprisingly, across all sensitivity analyses, the portfolio approach significantly improves eco-efficiency over the silo approach; the intuition behind this result is that the portfolio approach allows departments with low-cost opportunities for environmental reductions to internally compensate other departments that have high-cost reduction opportunities, as seen with the corn, electricity, and paperboard categories. Thus, EPP managers are able to more efficiently seize impact-reduction opportunities by more effectively managing capital resources across purchasing departments.

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DISCUSSION The reduced costs of the HSA−PPO method have enabled a portfolio-level assessment of environmental reduction opportunities available across purchased-product categories. In doing so, this study demonstrates that strategically coordinating and managing environmentally preferable procurement across the product portfolio can achieve substantially greater benefits than the traditional silo EPP approach. Despite these differences, both approaches lead to significant eco-efficiency improvements under the HSA−PPO method compared to traditional purchases. Although the HSA−PPO method was demonstrated within a breakfast cereal manufacturing firm context, the approach is general and may be applied to any industry and product category of interest. The HSA−PPO method enables the development of clear quantitative decision signals to SSCM and EPP decision makers regarding optimal purchases of green products to reach desired organizational performance. There are strong benefits to the HSA−PPO approach, but several limitations exist. For a discussion of limitations related to the HSA method, including impact leakage and trade-offs, refer to Pelton and Smith (2015).52 One of the primary limitations in the construction of the process LCA models is with regard to characterizing the relative water impacts for each product category. Due to the use of USLCI data in the life-cycle inventories of several products, including corn and wheat grain, water-depletion impacts are systematically underestimated in these categories. Consequently, water-depletion impacts are dominated by electricity inputs, which instead relies on data from Ecoinvent (see the Supporting Information for LCI details). With regard to the PPO approach, the optimal allocation among alternative product options will vary depending on the relative prices of product options; therefore, the approach is unable to provide once-and-for-all optimal results over time unless buyers are able to lock in fixed prices through long-term contracts. Using fixed contractual prices over time would smooth optimization results, but it is possible companies may be able to achieve greater savings (in impact or spending) if the optimization is iteratively run as market prices change,

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.5b06289. H


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Additional details on nomenclature, methodological steps and applications, model parameters and results, attribute definitions, life-cycle inventories, and a description of process LCA model assumptions. Tables showing hotspot scenario analysis procurement portfolio optimization methodological steps; variability in percent reductions and increments in total product option impact across all product attributes; selected product options and corresponding product physical units; sensitivity analysis of different organizational procurement budget scenarios; eco-efficiency comparison between silo and portfolio procurement approaches against baseline ecoefficiency values for different attribute pricing scenarios; eco-efficiency sensitivity analysis for alternative spend and alternative minimum and maximum hotspot percentage values; hotspot scenario analysis results and characterization; baseline and sensitivity analysis parameters; total GWP impact characterization; shadow prices on budget and physical unit constraints and sensitivity of shadow price estimates; containerboard, cleaning compound, plastic film, corn, wheat, plastic bag, and electricity environmental attribute definitions; life-cycle inventories of cleaning compounds, plastic films, containerboard, wheat, and electricity; plastic film baseline input assumption; electric energy, wind electricity, and thermal energy efficiency; alternative fossil, recycled, and biobased resin types; forest production, manufacturing, corrugated board, container board mill, and paperboard converting plant attributes; baseline input assumptions; corrugated board average hotspot contribution; baseline composition of 1 kg corrugated and paperboard boxes; FEFCO electricity input values for varying amounts of virgin and recycled fiber content; inventory input functions; net impact of switching from a baseline 35% recycled content to 75% recycled content due solely to the marginal difference in co-product credits and allocations between the two board compositions; composition of 1 kg corrugated and paperboard boxes for 75% recycled content attribute (i.e., 25% virgin, 75% recycled content); and average hotspot contribution to plastic film impacts and cleaning compounds. (PDF)

AUTHOR INFORMATION

Corresponding Author

*Phone: (612)-624-6755; e-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors acknowledge the Global Environmental Management Initiative (www.gemi.org) who provided funding (no. 42904-36834) for this study as well as access to sustainability and procurement managers of member companies throughout the development of the product category streamlined life-cycle assessments.

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Optimizing Eco-Efficiency Across the Procurement Portfolio

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